• DocumentCode
    2142400
  • Title

    Models and methods for prediction problem of evolving graphs

  • Author

    Chapanond, Anurat ; Krishnamoorthy, Mukkai S.

  • Author_Institution
    Comput. Sci. Dept. Rensselaer Polytech. Inst. Troy, New York, NY
  • fYear
    2008
  • fDate
    17-20 June 2008
  • Firstpage
    188
  • Lastpage
    190
  • Abstract
    This paper concentrates on the prediction problem of evolving graphs. We provide five new models and methods for prediction problem of evolving graphs. We experiment each method on real-world evolving graph data which are football competition data, file sharing data, Enron e-mail data, and Eurovision data. Experimental results show that our prediction methods can predict the result with higher accuracy than the random prediction.
  • Keywords
    graph theory; prediction theory; Enron e-mail data; Eurovision data; file sharing data; football competition data; prediction problem; real-world evolving graph; Artificial intelligence; Computer science; Government; Information analysis; Internet; Partial response channels; Peer to peer computing; Predictive models; Statistical analysis; Uniform resource locators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligence and Security Informatics, 2008. ISI 2008. IEEE International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-4244-2414-6
  • Electronic_ISBN
    978-1-4244-2415-3
  • Type

    conf

  • DOI
    10.1109/ISI.2008.4565052
  • Filename
    4565052